code: def test_Cifar10Rec(cifar10):
      dataiter = mx.io.ImageRecordIter(
          path_imgrec=os.path.join(cifar10, "cifar", "train.rec"),
          mean_img=os.path.join(cifar10, "cifar", "cifar10_mean.bin"),
          rand_crop=False,
          and_mirror=False,
          shuffle=False,
          data_shape=(3, 28, 28),
          batch_size=100,
          preprocess_threads=4,
          prefetch_buffer=1,
      )
      labelcount = [0 for i in range(10)]
      batchcount = 0
      for batch in dataiter:
          npdata = batch.data[0].asnumpy().flatten().sum()
          sys.stdout.flush()
          batchcount += 1
          nplabel = batch.label[0].asnumpy()
          for i in range(nplabel.shape[0]):
              labelcount[int(nplabel[i])] += 1
      for i in range(10):
          assert labelcount[i] == 5000
  
imports: import mxnet
  import mxnet.ndarray
  from mxnet.test_utils import *
  from mxnet.base import MXNetError
  import numpy
  import os
  import gzip
  import pickle
  import time
  import sys
  from common import assertRaises
  import pytest
  from itertools import zip_longest
label_desc: Use image node_id 3 for calling a global function with example usage: test_Cifar10Rec(cifar10) without return types